Abstract
Unexpected disruptions commonly occur in the railway network, causing delays, and extra cost for operators and inconvenience for passengers by missing their connection and facing overcrowded trains. This paper presents a passenger-centric approach for timetable rescheduling in case of disruption. We study a railway system in which passengers are free to choose their itinerary and compete over limited train capacity. We explicitly model the passengers’ decisions using a choice model. We propose a multi-objective algorithmic approach to solve the problem. Service punctuality, operating cost, and passengers’ inconvenience are selected as objectives. Computational experiments are performed on the Swiss and Dutch railway networks. The results demonstrate the performance of the algorithm in finding high-quality solutions in a computationally efficient manner.
Highlights
Dealing with disruption is an inevitable part of the railway’s daily operations
In this paper, we propose an algo rithmic framework to design a disposition timetable taking into account the train capacity
This paper introduces an algorithmic framework to design the disposition timetable, taking into account train’s capacity
Summary
Dealing with disruption is an inevitable part of the railway’s daily operations. Events such as open-track blockade, train station shutdown, and adverse weather conditions interrupt rail service. iteAs reported in Riden de Treinen (2021), the Dutch railway faced nine disruptions per day between 2011 and 2021. The operator plans a disposition timetable to restore the train service while minimizing passengers’ inconvenience. Passengers’ behavior is implicitly considered in the disposition timetable aimed to minimize delays and cancelations of trains, see, for example, Narayanaswami and Rangaraj (2013), Louwerse and Huisman (2014), Veelenturf et al (2016a) and, Ghaemi et al (2018). Passengers assignment models are well-studied problems to predict travelers’ behavior, see, Binder et al (2017a) and Zhu and Goverde (2020a) These models provide insight about the train occupancy and enable the decision-maker to comprehend the service quality perceived by travelers. This paper presents an algorithmic framework to design the disposition timetable when passengers could freely choose their itinerary, and the train ca pacity is limited.
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